Tag: Type I Error
In statistics, Type 1 and Type 2 errors relate to inaccurate conclusions in tests. Type 1 is a false positive, rejecting a true idea, while Type 2 is a false negative, accepting a false idea. Balancing these errors is essential for valid study results.
In statistical hypothesis testing, the null hypothesis asserts a lack of effect and serves as a baseline for evaluation. Specific tests are employed to assess evidence, leading to either the rejection or the failure to reject this initial assumption. This methodology is pivotal in both scientific inquiry and rational decision-making.